Biology subjects

Rosalie, M.

Publications and source records attributed to Rosalie, M..

3 recordsLinked to original sources

bioRxiv2025

Modelling the dynamics of transposable elements in genomes under asexual reproduction using agent-based model

Transposable elements (TEs) are abundantly present in eukaryotic genomes and can be likened to parasites colonizing a genome due to their properties. From this perspective, a population-based approach has been developed to model interactions between TEs and a genome population. The distribution of TEs within a population of genomes is studied over the long term to understand the mechanisms allowing TEs to persist despite their deleterious effects on genomes. Under this single restrictive assumption, the results show that the population of TEs can persist for a very long time within the genome population, when the genome population is highly diverse in terms of the distribution of TEs quantities. When there is no mechanism for silencing TEs, the proposed model of asexual reproduction either purges TEs or leads to co-extinction of genomes and TEs. On the other hand, with a high proportion of silenced TEs, the population of TEs can be maintained for a long time in the population of genomes.

genetics↗

bioRxiv2025

Anticipating invasion of parasite with graph theory: Dryocosmus kuriphilus, a threat for Castanea sativa

The increase in world trade contributed to a rise in the number of insect biological invasions. The colonisation success of herbivorous pests depends mostly on the abundance of vegetal resource across the newly invaded territory. The explicit spatial representation of plant distribution offers a cost-effective approach to anticipate the spread of herbivorous insects over areas with fragmented and heterogeneous vegetal populations. In this article, we focus on the case of the recent invasion of chestnut trees (Castanea sativa) of the French Eastern Pyrenees by its most virulent pest, the gall-forming parasite Dryocosmus kuriphilus. Using tools from graph theory and available public data on the mesh size and distribution of chestnut trees, we model the spatial distribution of the pest resource across natural forests. In this framework, a graph provides a mapping of 1 km2 quadrats that constitute the territory. Quadrats are grouped to form communities, which are areas with homogeneous chestnut tree distribution, and in which the risk of parasite infestation and propagation is similar. Graph traversal algorithms then measure the vulnerability and the dangerousness of each patch, defined as their susceptibility to become infected and to contribute to the pest propagation. Such a spatial assessment of the invasion risk provides unique insights into potential propagation scenarios, improving the early detection and spread monitoring of these insect invaders. Author summary

ecology↗

bioRxiv2024

Unravelling the bottom-up and top-down control of a worldwide chestnut tree pest invader through integrative ecological genomics

Biological invasions have become a major threat to all agro-ecosystems. Estimating the bottom-up and top-down forces controlling the spread of invasive insects is a key challenge to lessen their burden on crops, forestry, and biodiversity. We combined ecological, metabarcoding and population genomics analyses with an integrative modelling of the invasion of a global insect pest to identify the impacts of its chestnut tree resource, natural enemies and biological control agent in Eastern Pyrenees. The host tree frequency and genomic variation associated with common resistance pathways had effects 4-10 times greater than the native hyperparasite community on the pests invasion potential (R0). The >90% field rates of hyperparasitism by the control agent and the associated 80% reduction in pest infestation are likely to be deceptive as our modelling consistently predicts their long-term coexistence with periodic re-emergences. Such a persistent co-invasion scenario calls for a thorough assessment of the impact of these global pest and control agent on natural forest ecosystems.

systems biology↗